@article{8e3fae5b96b34ab58946e1f4f6340737,
title = "Integrative transcriptome imputation reveals tissue-specific and shared biological mechanisms mediating susceptibility to complex traits",
abstract = "Transcriptome-wide association studies integrate gene expression data with common risk variation to identify gene-trait associations. By incorporating epigenome data to estimate the functional importance of genetic variation on gene expression, we generate a small but significant improvement in the accuracy of transcriptome prediction and increase the power to detect significant expression-trait associations. Joint analysis of 14 large-scale transcriptome datasets and 58 traits identify 13,724 significant expression-trait associations that converge on biological processes and relevant phenotypes in human and mouse phenotype databases. We perform drug repurposing analysis and identify compounds that mimic, or reverse, trait-specific changes. We identify genes that exhibit agonistic pleiotropy for genetically correlated traits that converge on shared biological pathways and elucidate distinct processes in disease etiopathogenesis. Overall, this comprehensive analysis provides insight into the specificity and convergence of gene expression on susceptibility to complex traits.",
author = "Wen Zhang and Georgios Voloudakis and Rajagopal, {Veera M.} and Ben Readhead and Dudley, {Joel T.} and Schadt, {Eric E.} and Bj{\"o}rkegren, {Johan L.M.} and Yungil Kim and Fullard, {John F.} and Hoffman, {Gabriel E.} and Panos Roussos",
note = "Funding Information: The authors would like to thank: Scott Dickinson, Alvaro Barbeira, and Hae Kyung Im for providing valuable feedback on their PrediXcan and S-PrediXcan pipelines; David L. Morris and Timothy J. Vyse for providing access to GWAS summary results in systemic lupus erythematosus; Ping Zeng and Xiang Zhou for providing suggestions on proper implementations of their BSLMM and DPR pipelines; Hon-Cheong So for providing the top-100 candidate lists of their drug repositioning analysis for psychiatric traits; and the authors Ethan Bahl, Tanner Koomar, and Jacob J Michaelson of the freely available (under the GNU GPLv3 license) cerebroViz R package used to generate an image that served as the basis of the brain artwork in Fig. 1a. This work was supported by the National Institutes of Health (NIH) grants R01AG050986 (P.R.), R01MH109897 (P.R. and E.E.S.) and R01MH109677 (P.R.), Leon Levy Foundation (G.V.; Leon Levy Fellowship in Neuroscience) and the Veterans Affairs Merit grants BX002395 and BX004189 (P.R.). Further, this work was supported in part through the computational resources and staff expertize provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Publisher Copyright: {\textcopyright} 2019, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.",
year = "2019",
month = dec,
day = "1",
doi = "10.1038/s41467-019-11874-7",
language = "English (US)",
volume = "10",
journal = "Nature communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}